Answer:31.4cm
Step-by-step explanation:
Circumference=2×π×(diameter/2)
Circumference=2×3.14×10/2
Circumference=(2×3.14×5)
Circumference=31.
<u>We'll assume the quadratic equation has real coefficients</u>
Answer:
<em>The other solution is x=1-8</em><em>i</em><em>.</em>
Step-by-step explanation:
<u>The Complex Conjugate Root Theorem</u>
if P(x) is a polynomial in x with <em>real coefficients</em>, and a + bi is a root of P(x) with a and b real numbers, then its complex conjugate a − bi is also a root of P(x).
The question does not specify if the quadratic equation has real coefficients, but we will assume that.
Given x=1+8i is one solution of the equation, the complex conjugate root theorem guarantees that the other solution must be x=1-8i.
Answer:
Distance =√(x₁ - y₁)²+ (x₂ - y₂)² = √97 = 9.85
Step-by-step explanation:
The Matrix X and Y could also be referred to as vectors in Rⁿ dimensions.
if Vector X = ( x₁ , x₂) and Vector Y = (y₁ , y₂)
then, Distance (X-Y) = ||X-Y|| = √(x₁ - y₁)²+ (x₂ - y₂)²
where, x₁ = 8, x₂ = -5 and y₁ = -1 , y₂ = -9
Distance = √(8 - (-1))²+ (-5 - (-9))² = √9² + 4² =√97 = 9.85
Using remainder theorem, we get:
Substitute t = 5 into the equation:
Thus, we get a remainder of 93 or (A)
Answer:
c. The Mean of Normal Distribution is related to the average of the data set. The Standard deviation is related to data variation.
Step-by-step explanation:
(a) No, mean don't tell us how much the data deviate from the average, Standard deviation tells us. So, Option (a) is incorrect.
(b) No, mean is greatly affected by extreme values. But Median is good to measure central tendency when there is outlier present in data. So, Option (b) is also incorrect.
(c) Here Mean and Standard deviation are correctly defined. Hence, this is only the correct answer.
(d) No, It is the definition of mean not of Standard Deviation. So, this option is also incorrect.
Further, Mean is used to measure the central tendency of data which represents the whole data in the best way. It can be found as the ratio of the sum of all the observations to the total number of observations.
